The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation

Abstract

Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited corticocortical spectral responses at high-gamma frequencies (CCSR HG , 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSR HG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.

Brain-scale cortico-cortical functional connectivity in the delta-theta band is a robust signature of conscious states: an intracranial and scalp EEG study

“…A recent iEEG study used single-pulse electrical brain stimulations to describe their overall propagation across the different regions of the brain and the different sleep stages. This study suggest that the regulation of conscious awareness and sleep is associated with significant differences in the balance of neural propagation across a wide frontal-parietal network despite the uniform functional connectivity we reported in the present study 55 .…”

6D dynamic tractography visualizes the effective connectivity supporting specific linguistic stages in the developing brain

“…However, Granger causality cannot consistently distinguish direct versus indirect connectivity. Early CCSRs are a valuable measure to quantify the strength of long-range direct effective connectivity 39,41 , but do not reveal the anatomical white matter structure which supports the observed connectivity. Conversely, DWI-based tractography is a powerful tool to characterize anatomical white matter networks between two regions 11 , but does not measure the directionality or function of the pathway.…”

“…To quantify inter-lobar effective connectivity, we measured cortico-cortical spectral responses (CCSRs) elicited by weak single-pulse electrical stimulation at two adjacent electrode contacts 39 . While task-related high-gamma connectivity measures can demonstrate statistical covariation, they do not provide causal evidence of direct connectivity.…”

“…While task-related high-gamma connectivity measures can demonstrate statistical covariation, they do not provide causal evidence of direct connectivity. Both CCSRs and cortico-cortical evoked potentials (CCEPs) are powerful tools to quantify the strength and dynamics of effective connectivity in each direction between two remote regions [39][40][41][42][43] . The two measures generally re ect the same underlying neuronal process but highlight different aspects of the recorded signal.…”

“…This notion is supported by the observation that the peak latency of such early responses is correlated with the surface distance as well as the underlying white matter streamline length on diffusion-weighted imaging (DWI) tractography [48][49][50] . Late, low-frequency band CCSRs, roughly corresponding to the late CCEP component (also known as N2), are suggested to mainly indicate post-excitatory neuronal inhibition 39,44,46 and represent an indirect measure of inhibitory networks that govern effective connectivity.…”